Controllable Fake Document Infilling for Cyber Deception
This addresses the need for more effective cyber deception tools to deter malicious intrusion by creating varied and realistic fake documents, though it appears incremental as it builds on prior work with a novel method.
The paper tackles the problem of generating context-aware fake documents for cyber deception by proposing Fake Document Infilling (FDI), which outperforms baselines in producing believable fakes with moderate modifications to protect critical information.
Recent works in cyber deception study how to deter malicious intrusion by generating multiple fake versions of a critical document to impose costs on adversaries who need to identify the correct information. However, existing approaches are context-agnostic, resulting in sub-optimal and unvaried outputs. We propose a novel context-aware model, Fake Document Infilling (FDI), by converting the problem to a controllable mask-then-infill procedure. FDI masks important concepts of varied lengths in the document, then infills a realistic but fake alternative considering both the previous and future contexts. We conduct comprehensive evaluations on technical documents and news stories. Results show that FDI outperforms the baselines in generating highly believable fakes with moderate modification to protect critical information and deceive adversaries.